Without a formal methodology extracting entities from business descriptions, a
business requirement in the real world cannot be abstracted correctly into an entity-relationship
schema. Once core entities are discovered, we can obtain an Entity-Relationship
Diagram (ERD) by inserting relationships between/among the relevant entities and by
aggregating some attributes into one of the entities or relationships. There have been so
many studies on formal guidelines for extracting entities from business descriptions.
Most of them adopt a knowledge-based approach which consults a knowledge base to
recommend entity candidates. However, the knowledge-based approach usually fails to
construct the most appropriate ERD for a given business domain. The approach performs
the entity extraction on the stiff premise that an object would be classified as an entity if
it happen to be classified as an entity once or more in past applications. The previous
studies did not consider the flexibility in the object classification that even the same object
could be regarded as either an entity or an attribute according to the various concerns
of field workers. In this paper, we discuss some limitations of the previous researches
on object classification and propose a new methodology for flexible entity extraction.
To evaluate the practicality of the devised methodology, we developed a tool
for the methodology and performed a case study on option trading applications with the
tool.